Machine Learning courses

1335 Courses

AWS Skill Builder

AWS Escape Room: Exam Prep for AWS Certified AI Practitioner (AIF-C01 - English)

AWS Escape Room: Exam Prep for AWS Certified AI Practitioner (AIF-C01 - English) AWS Escape Room: Exam Prep for AWS Certified AI Practitioner (AIF-C01) is a 2-hour 3D virtual escape room game for learners preparing for AWS Certified AI Practitioner (AIF-C01). The escape room is one step in the 4-step plan that you can use to prepare for your exa.

LinkedIn Learning

Become an RPA Developer

Become an RPA Developer Using robotic process automation (RPA), organizations can now digitize and transform an array of business processes and functions. In this learning path, delve into the basics of RPA, process mining, and other forms of AI and cognitive tech that can optimize your business processes through automation. Categories: Artifi.

LinkedIn Learning

Prepare for the Microsoft Azure AI Fundamentals (AI-900) Certification

Prepare for the Microsoft Azure AI Fundamentals (AI-900) Certification The Azure AI Fundamentals exam measures your understanding of AI fundamentals, Azure AI services, machine learning models, data preparation and processing, and best practices for AI. The courses in this learning path align with these topics to provide comprehensive preparation.

LinkedIn Learning

Develop Your Skills with the OpenAI API

Develop Your Skills with the OpenAI API The popularity of OpenAI's powerful machine learning models enables developers to create amazing AI-powered applications. The OpenAI API serves as the bridge to these powerful models. Through this learning path, developers can explore the OpenAI API's capabilities and start building powerful AI applications.

LinkedIn Learning

Develop with Python for AI and Machine Learning

AWS Skill Builder

AWS SimuLearn: TensorFlow and Computer Vision

AWS SimuLearn: TensorFlow and Computer Vision AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS SimuLearn: Te.

AWS Skill Builder

AWS SimuLearn: Set Up an ML Environment

AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS SimuLearn: Set Up an ML Environment In this AWS SimuLearn assi.

Pluralsight

Responsible AI for Developers: Interpretability & Transparency

Responsible AI for Developers: Interpretability & Transparency This course, Responsible AI for Developers: Interpretability & Transparency, introduces key concepts of AI interpretability and transparency, emphasizing their importance for developers and engineers. Provided by Pluralsight, it explores practical methods and tools to help achieve in.

Pluralsight

Introduction to Azure AI Services

Introduction to Azure AI Services Azure AI services enable you to build intelligent enterprise apps that integrate with your existing business workflows and technologies. In this course, "Introduction to Azure AI Services," you will explore the various AI services available on the Azure platform and understand how to integrate them with your own.

Pluralsight

Image Analysis and OCR with Azure AI Vision

Image Analysis and OCR with Azure AI Vision Understanding and leveraging advanced AI capabilities can be challenging, especially for beginners. In this course, Image Analysis and OCR with Azure AI Vision, you’ll learn to effectively use Azure Cognitive Services for various vision-related tasks. First, you’ll explore how to leverage image analy.

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Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Voice assistant Alisa. This system, without human help, will always find the answer to any question of interest, turn on music, answer the call and much more.

Selecting relevant advertising in browsers is not an easy process for a person, but it is quick for a computer. The system will analyze the viewing data and select what a particular user will like. The same system is used on various marketplaces - products that a person viewed or purchased are offered.

Chatbots in various dialogues. For example, many banks use bots to solve customer problems. It's convenient and fast.

Data security: Machine learning models can identify data security vulnerabilities before they become breaches. By analyzing past experiences, machine learning models can predict future high-risk actions so that risk can be mitigated proactively.

Finance: Banks, trading brokers and fintech firms use machine learning algorithms to automate trading and provide financial advisory services to investors. Bank of America uses chatbot Erica to automate customer support.

Healthcare: Machine learning is used to analyze massive medical data sets to speed up the discovery of treatments and cures, improve patient outcomes, and automate routine processes to prevent human errors. For example, IBM Watson uses data mining to provide doctors with data they can use to personalize patient care.

Fraud detection: AI is used in the finance and banking sector to autonomously analyze large numbers of transactions to identify fraudulent activities in real time. Technology services company Capgemini says fraud detection systems using machine learning and analytics reduce fraud investigation time by 70% and increase detection accuracy by 90% .

Retail: AI researchers and developers are using machine learning algorithms to develop AI recommendation engines that make relevant product suggestions based on shoppers' past choices, as well as historical, geographic and demographic data.

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

Average knowledge of statistics and probability.

Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

Understanding Calculus.

Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!